High Hepatic leukemia factor expression indicates a favorable survival in glioma patients

Transcriptional regulation of genetic variants in the SLC40A1 promoter

Solute carrier 40A1 (SLC40A1) encodes ferroportin, which is the only known transmembrane protein that exports elemental iron from mammalian cells and is essential for iron homeostasis. Mutations in SLC40A1 are associated with iron-overload disorders. In addition to ferroportin diseases, SLC40A1 expression is downregulated in various cancer types. Despite the clinical significance of the SLC40A1 transporter, only a few studies have investigated genetic variants in SLC40A1. The present study was performed to identify genetic variations in the SLC40A1 promoter and functionally characterize each variant using in vitro assays. We investigated four haplotypes and five variants in the SLC40A1 promoter. We observed that haplotype 3 (H3) had significantly lower promoter activity than H1, whereas the activity of H4 was significantly higher than that of H1. Luciferase activity of H2 was comparable to that of H1. In addition, four variants of SLC40A1, c.-1355G>C, c.-662C>T, c.-98G>C, and c.-8C>G, showed significantly increased luciferase activity compared to the wild type (WT), whereas c.-750G>A showed significantly decreased luciferase activity compared to the WT. Three transcription factors, cAMP response element-binding protein-1 (CREB-1), chicken ovalbumin upstream promoter transcription factor 1, and hepatic leukemia factor (HLF), were predicted to bind to the promoter regions of SLC40A1 near c.-662C>T, c.-98G>C, and c.-8C>G, respectively. Among these, CREB-1 and HLF bound more strongly to the variant sequences than to the WT and functioned as activators of SLC40A1 transcription. Collectively, our findings indicate that the two SLC40A1 promoter haplotypes affect SLC40A1 transcription, which is regulated by CREB-1 and HLF.

HLF promotes ovarian cancer progression and chemoresistance via regulating Hippo signaling pathway

Hepatic leukemia factor (HLF) is aberrantly expressed in human malignancies. However, the role of HLF in the regulation of ovarian cancer (OC) remains unknown. Herein, we reported that HLF expression was upregulated in OC tissues and ovarian cancer stem cells (CSCs). Functional studies have revealed that HLF regulates OC cell stemness, proliferation, and metastasis. Mechanistically, HLF transcriptionally activated Yes-associated protein 1 (YAP1) expression and subsequently modulated the Hippo signaling pathway. Moreover, we found that miR-520e directly targeted HLF 3'-UTR in OC cells. miR-520e expression was negatively correlated with HLF and YAP1 expression in OC tissues. The combined immunohistochemical (IHC) panels exhibited a better prognostic value for OC patients than any of these components alone. Importantly, the HLF/YAP1 axis determines the response of OC cells to carboplatin treatment and HLF depletion or the YAP1 inhibitor verteporfin abrogated carboplatin resistance. Analysis of patient-derived xenografts (PDXs) further suggested that HLF might predict carboplatin benefits in OC patients. In conclusion, these findings suggest a crucial role of the miR-520e/HLF/YAP1 axis in OC progression and chemoresistance, suggesting potential therapeutic targets for OC.

Developing a 5-gene prognostic signature for cervical cancer by integrating mRNA and copy number variations

Background

Cervical cancer is frequently detected gynecological cancer all over the world. This study was designed to develop a prognostic signature for an effective prediction of cervical cancer prognosis.

Methods

Differentially expressed genes (DEGs) were identified based on copy number variation (CNV) data and expression profiles from different databases. A prognostic model was constructed and further optimized by stepwise Akaike information criterion (stepAIC). The model was then evaluated in three groups (training group, test group and validation group). Functional analysis and immune analysis were used to assess the difference between high-risk and low-risk groups.

Results

The study developed a 5-gene prognostic model that could accurately classify cervical cancer samples into high-risk and low-risk groups with distinctly different prognosis. Low-risk group exhibited more favorable prognosis and higher immune infiltration than high-risk group. Both univariate and multivariate Cox regression analysis showed that the risk score was an independent risk factor for cervical cancer.

Conclusions

The 5-gene prognostic signature could serve as a predictor for identifying high-risk cervical cancer patients, and provided potential direction for studying the mechanism or drug targets of cervical cancer. The integrated analysis of CNV and mRNA expanded a new perspective for exploring prognostic signatures in cervical cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09291-z.